Written by Tim Deakin

25th March 2025

• Cyber Security
• Incident Response

Share this article

As technology advances at a breakneck speed, modern businesses have the unenviable task of balancing the need to keep pace with change alongside a duty to manage risk and exercise caution. While Artificial Intelligence (AI) is emerging as a powerful tool for businesses it also raises as many questions as it does answers – particularly when it comes to cyber security and data protection. 

There is no doubt, however, that AI’s role in cybersecurity risk management will only grow in the coming months and years. So, taking the time to understand it’s potential is essential in 2025. Here’s an introduction for business leaders:

Spotting risks before they become breaches

One of the biggest advantages AI brings to cybersecurity is the ability to detect threats early. Sometimes before they even happen. Instead of relying solely on known attack signatures or fixed rules, AI systems can now learn to spot unusual patterns that indicate a potential threat using the vast amounts of data available to them.

Take, for example, an employee logging in at an odd hour from an unfamiliar location. On its own, it might not raise flags. But when combined with other subtle indicators – like unexpected data downloads or access to files outside their usual scope – AI can flag it for review long before damage is done.

Real-time responses to fast-moving threats

In cybersecurity, time is always of the essence. The longer a threat goes undetected, the more damage it will typically cause. Although human cybersecurity experts are invaluable and perform an essential role, they do need to sleep at some point each day. 

AI tools, on the other hand, never get tired and never need breaks. They can work around the clock, automatically responding to threats in real time. Whether that’s isolating a compromised device, blocking suspicious traffic, or alerting security teams to investigate, these systems can drastically reduce response times. Importantly, they can also raise issues to cyber security consultants who are able to then interpret the data and investigate a potential issue.

This kind of rapid response is especially valuable for defending against phishing attacks, ransomware, and zero-day exploits, where early action can prevent widespread disruption.

Making sense of mountains of data

Security teams today are drowning in alerts and logs. Sifting through all that information manually is time-consuming – and often impossible for small teams with lots of responsibilities. AI can help to lighten the load on infosec teams by filtering the noise, prioritising the most urgent threats and highlighting connections that a human might miss.

Machine learning models trained on cybersecurity data can continuously improve, becoming better at spotting what matters and reducing false positives. This means security teams can focus on real issues, not endless alert fatigue.

Strengthening compliance and governance

With regulations and information security standards such as ISO 27001 tightening the requirements for data protection, businesses need to ensure they remain compliant at all times. AI can assist by automating tasks such as monitoring access controls, logging changes and flagging policy violations.

Rather than relying on infrequent audits, organisations can use AI to maintain a near-constant view of their compliance status, reducing risk and demonstrating accountability to regulators and customers alike.

AI doesn’t replace people. It supports them

There’s a common misconception that AI tools are designed to replace security analysts or infosec professionals. In reality, the most effective cybersecurity strategies combine the best of both: AI to handle the time-intensive heavy lifting, and human expertise to provide context and decision-making.

AI can help spot an anomaly, but a human still needs to determine whether it’s a genuine threat or a false alarm . . . and then decide what to do next. When used correctly, AI makes security teams more efficient rather than redundant.

What cybersecurity leaders should focus on

If you’re responsible for cybersecurity in your organisation, here are a few steps to consider:

• Evaluate your current tools – Are they able to keep pace with today’s threats? If not, AI-powered platforms may be worth exploring.
• Review your data – AI is only as good as the data it learns from. Make sure your logs and telemetry are accurate, consistent, and accessible.
• Train your team – As AI becomes more integrated into cybersecurity tools, ensure your staff are confident using them and know how to interpret the outputs.
• Keep humans in the loop – Use AI to support decision-making, not replace it. Balance automation with oversight – whether that is internal or through an external cybersecurity consultant.

Is your organisation looking to manage risk more effectively? Not sure where to start with your human or AI support? Get in touch with the team at SRM today. Contact us.